TY - GEN
T1 - Automated Vulnerability Testing and Detection Digital Twin Framework for 5G Systems
AU - Dauphinais, Danielle
AU - Zylka, Michael
AU - Spahic, Harris
AU - Shaik, Farhan
AU - Yang, Jingda
AU - Cruz, Isabella
AU - Gibson, Jakob
AU - Wang, Ying
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Efficient and precise detection of vulnerabilities in 5G protocols and implementations is crucial for ensuring the security of its application in critical infrastructures. However, with the rapid evolution of 5G standards and the trend towards softwarization and virtualization, this remains a challenge. In this paper, we present an automated Fuzz Testing Digital Twin Framework that facilitates systematic vulnerability detection and assessment of unintended emergent behavior, while allowing for efficient fuzzing path navigation. Our framework utilizes assembly-level fuzzing as an acceleration engine and is demonstrated on the flagship 5G software stack: srsRAN. The introduced digital twin solution enables the simulation, verification, and connection to 5G testing and attack models in real-world scenarios. By identifying and analyzing vulnerabilities on the digital twin platform, we significantly improve the security and resilience of 5G systems, mitigate the risks of zero-day vulnerabilities, and provide comprehensive testing environments for current and newly released 5G systems.
AB - Efficient and precise detection of vulnerabilities in 5G protocols and implementations is crucial for ensuring the security of its application in critical infrastructures. However, with the rapid evolution of 5G standards and the trend towards softwarization and virtualization, this remains a challenge. In this paper, we present an automated Fuzz Testing Digital Twin Framework that facilitates systematic vulnerability detection and assessment of unintended emergent behavior, while allowing for efficient fuzzing path navigation. Our framework utilizes assembly-level fuzzing as an acceleration engine and is demonstrated on the flagship 5G software stack: srsRAN. The introduced digital twin solution enables the simulation, verification, and connection to 5G testing and attack models in real-world scenarios. By identifying and analyzing vulnerabilities on the digital twin platform, we significantly improve the security and resilience of 5G systems, mitigate the risks of zero-day vulnerabilities, and provide comprehensive testing environments for current and newly released 5G systems.
KW - 5G Security
KW - Assembly-Level
KW - Digital Twin
KW - Fuzzing
KW - Testing Framework
UR - http://www.scopus.com/inward/record.url?scp=85162155266&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85162155266&partnerID=8YFLogxK
U2 - 10.1109/NetSoft57336.2023.10175496
DO - 10.1109/NetSoft57336.2023.10175496
M3 - Conference contribution
AN - SCOPUS:85162155266
T3 - 2023 IEEE 9th International Conference on Network Softwarization: Boosting Future Networks through Advanced Softwarization, NetSoft 2023 - Proceedings
SP - 308
EP - 310
BT - 2023 IEEE 9th International Conference on Network Softwarization
A2 - Bernardos, Carlos J.
A2 - Martini, Barbara
A2 - Rojas, Elisa
A2 - Verdi, Fabio Luciano
A2 - Zhu, Zuqing
A2 - Oki, Eiji
A2 - Parzyjegla, Helge
T2 - 9th IEEE International Conference on Network Softwarization, NetSoft 2023
Y2 - 19 June 2023 through 23 June 2023
ER -